{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 请在Pima Indians Diabetes Data Set（皮马印第安人糖尿病数据集）进行分类器练习"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1、训练数据和测试数据分割（随机选择20%的数据作为测试集）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 首先 import 必要的模块\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "#竞赛的评价指标为logloss\n",
    "from sklearn.metrics import log_loss  \n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
       "0            6      148             72             35        0  33.6   \n",
       "1            1       85             66             29        0  26.6   \n",
       "2            8      183             64              0        0  23.3   \n",
       "3            1       89             66             23       94  28.1   \n",
       "4            0      137             40             35      168  43.1   \n",
       "\n",
       "   DiabetesPedigreeFunction  Age  Outcome  \n",
       "0                     0.627   50        1  \n",
       "1                     0.351   31        0  \n",
       "2                     0.672   32        1  \n",
       "3                     0.167   21        0  \n",
       "4                     2.288   33        1  "
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读取数据\n",
    "# path to where the data lies\n",
    "train = pd.read_csv(\"diabetes.csv\")\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      "Pregnancies                 768 non-null int64\n",
      "Glucose                     768 non-null int64\n",
      "BloodPressure               768 non-null int64\n",
      "SkinThickness               768 non-null int64\n",
      "Insulin                     768 non-null int64\n",
      "BMI                         768 non-null float64\n",
      "DiabetesPedigreeFunction    768 non-null float64\n",
      "Age                         768 non-null int64\n",
      "Outcome                     768 non-null int64\n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.845052  120.894531      69.105469      20.536458   79.799479   \n",
       "std       3.369578   31.972618      19.355807      15.952218  115.244002   \n",
       "min       0.000000    0.000000       0.000000       0.000000    0.000000   \n",
       "25%       1.000000   99.000000      62.000000       0.000000    0.000000   \n",
       "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "              BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
       "count  768.000000                768.000000  768.000000  768.000000  \n",
       "mean    31.992578                  0.471876   33.240885    0.348958  \n",
       "std      7.884160                  0.331329   11.760232    0.476951  \n",
       "min      0.000000                  0.078000   21.000000    0.000000  \n",
       "25%     27.300000                  0.243750   24.000000    0.000000  \n",
       "50%     32.000000                  0.372500   29.000000    0.000000  \n",
       "75%     36.600000                  0.626250   41.000000    1.000000  \n",
       "max     67.100000                  2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 各属性的统计特性\n",
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(768, 9)"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pregnancies                 0\n",
       "Glucose                     0\n",
       "BloodPressure               0\n",
       "SkinThickness               0\n",
       "Insulin                     0\n",
       "BMI                         0\n",
       "DiabetesPedigreeFunction    0\n",
       "Age                         0\n",
       "Outcome                     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 判断数据有无空值\n",
    "train.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 从原始数据中分离输入特征x和输出y\n",
    "y = train['Outcome'].values\n",
    "X = train.drop('Outcome', axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(768,)"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(768, 8)"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(614, 8)"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将数据分割训练数据与测试数据\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 随机采样20%的数据构建测试样本，其余作为训练样本\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=33, test_size=0.2)\n",
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(614,)"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2、适当的特征工程"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（1）怀孕次数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2259e9d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数直方图\n",
    "fig=plt.figure(figsize=(17,5))\n",
    "plt.subplot(121)\n",
    "sns.distplot(X_train.Pregnancies.values, bins=30, kde=True)\n",
    "plt.title(\"Histogram of Pregnancies\");\n",
    "plt.xlabel('Value of Pregnancies', fontsize=12)\n",
    "plt.ylabel('Probability', fontsize=12)\n",
    "\n",
    "#怀孕次数散点图\n",
    "plt.subplot(122)\n",
    "plt.scatter(range(X_train.shape[0]), X_train[\"Pregnancies\"].values,color='orange')\n",
    "plt.title(\"Distribution of Pregnancies\");\n",
    "plt.xlabel('Count of Pregnancies', fontsize=12)\n",
    "plt.ylabel('Value of Pregnancies', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2233e05f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数直方图\n",
    "fig=plt.figure(figsize=(17,5))\n",
    "plt.subplot(121)\n",
    "sns.distplot(X_train.Glucose.values, bins=30, kde=True)\n",
    "plt.title(\"Histogram of Glucose\");\n",
    "plt.xlabel('Value of Glucose', fontsize=12)\n",
    "plt.ylabel('Probability', fontsize=12)\n",
    "\n",
    "#怀孕次数散点图\n",
    "plt.subplot(122)\n",
    "plt.scatter(range(X_train.shape[0]), X_train[\"Glucose\"].values,color='orange')\n",
    "plt.title(\"Distribution of Glucose\");\n",
    "plt.xlabel('Count of Glucose', fontsize=12)\n",
    "plt.ylabel('Value of Glucose', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "25以下存个别噪声点，应该去除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "#X_train=X_train[X_train[\"Glucose\"]>25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225a9f8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数直方图\n",
    "fig=plt.figure(figsize=(17,5))\n",
    "plt.subplot(121)\n",
    "sns.distplot(X_train.BloodPressure.values, bins=30, kde=True)\n",
    "plt.title(\"Histogram of BloodPressure\");\n",
    "plt.xlabel('Value of BloodPressure', fontsize=12)\n",
    "plt.ylabel('Probability', fontsize=12)\n",
    "\n",
    "#怀孕次数散点图\n",
    "plt.subplot(122)\n",
    "plt.scatter(range(X_train.shape[0]), X_train[\"BloodPressure\"].values,color='orange')\n",
    "plt.title(\"Distribution of BloodPressure\");\n",
    "plt.xlabel('Count of BloodPressure', fontsize=12)\n",
    "plt.ylabel('Value of BloodPressure', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "20以下存个别噪声点，应该去除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "#X_train=X_train[X_train[\"BloodPressure\"]>20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225ef65f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数直方图\n",
    "fig=plt.figure(figsize=(17,5))\n",
    "plt.subplot(121)\n",
    "sns.distplot(X_train.SkinThickness.values, bins=30, kde=True)\n",
    "plt.title(\"Histogram of SkinThickness\");\n",
    "plt.xlabel('Value of SkinThickness', fontsize=12)\n",
    "plt.ylabel('Probability', fontsize=12)\n",
    "\n",
    "#怀孕次数散点图\n",
    "plt.subplot(122)\n",
    "plt.scatter(range(X_train.shape[0]), X_train[\"SkinThickness\"].values,color='orange')\n",
    "plt.title(\"Distribution of SkinThickness\");\n",
    "plt.xlabel('Count of SkinThickness', fontsize=12)\n",
    "plt.ylabel('Value of SkinThickness', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "#X_train=X_train[X_train[\"SkinThickness\"]>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225be5898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数直方图\n",
    "fig=plt.figure(figsize=(17,5))\n",
    "plt.subplot(121)\n",
    "sns.distplot(X_train.Insulin.values, bins=30, kde=True)\n",
    "plt.title(\"Histogram of Insulin\");\n",
    "plt.xlabel('Value of Insulin', fontsize=12)\n",
    "plt.ylabel('Probability', fontsize=12)\n",
    "\n",
    "#怀孕次数散点图\n",
    "plt.subplot(122)\n",
    "plt.scatter(range(X_train.shape[0]), X_train[\"Insulin\"].values,color='orange')\n",
    "plt.title(\"Distribution of Insulin\");\n",
    "plt.xlabel('Count of Insulin', fontsize=12)\n",
    "plt.ylabel('Value of Insulin', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "#X_train=X_train[X_train[\"Insulin\"]<600]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225cf0eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数直方图\n",
    "fig=plt.figure(figsize=(17,5))\n",
    "plt.subplot(121)\n",
    "sns.distplot(X_train.BMI.values, bins=30, kde=True)\n",
    "plt.title(\"Histogram of BMI\");\n",
    "plt.xlabel('Value of BMI', fontsize=12)\n",
    "plt.ylabel('Probability', fontsize=12)\n",
    "\n",
    "#怀孕次数散点图\n",
    "plt.subplot(122)\n",
    "plt.scatter(range(X_train.shape[0]), X_train[\"BMI\"].values,color='orange')\n",
    "plt.title(\"Distribution of BMI\");\n",
    "plt.xlabel('Count of BMI', fontsize=12)\n",
    "plt.ylabel('Value of BMI', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "#X_train=X_train[X_train[\"BMI\"]>10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225db7748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数直方图\n",
    "fig=plt.figure(figsize=(17,5))\n",
    "plt.subplot(121)\n",
    "sns.distplot(X_train.DiabetesPedigreeFunction.values, bins=30, kde=True)\n",
    "plt.title(\"Histogram of DiabetesPedigreeFunction\");\n",
    "plt.xlabel('Value of DiabetesPedigreeFunction', fontsize=12)\n",
    "plt.ylabel('Probability', fontsize=12)\n",
    "\n",
    "#怀孕次数散点图\n",
    "plt.subplot(122)\n",
    "plt.scatter(range(X_train.shape[0]), X_train[\"DiabetesPedigreeFunction\"].values,color='orange')\n",
    "plt.title(\"Distribution of DiabetesPedigreeFunction\");\n",
    "plt.xlabel('Count of DiabetesPedigreeFunction', fontsize=12)\n",
    "plt.ylabel('Value of DiabetesPedigreeFunction', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "#X_train=X_train[X_train[\"DiabetesPedigreeFunction\"]<2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f22568eac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#怀孕次数直方图\n",
    "fig=plt.figure(figsize=(17,5))\n",
    "plt.subplot(121)\n",
    "sns.distplot(X_train.Age.values, bins=30, kde=True)\n",
    "plt.title(\"Histogram of Age\");\n",
    "plt.xlabel('Value of Age', fontsize=12)\n",
    "plt.ylabel('Probability', fontsize=12)\n",
    "\n",
    "#怀孕次数散点图\n",
    "plt.subplot(122)\n",
    "plt.scatter(range(X_train.shape[0]), X_train[\"Age\"].values,color='orange')\n",
    "plt.title(\"Distribution of Age\");\n",
    "plt.xlabel('Count of Age', fontsize=12)\n",
    "plt.ylabel('Value of Age', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "相关性分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225912208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pregnancies and Age = 0.54\n"
     ]
    }
   ],
   "source": [
    "#get the names of all the columns\n",
    "cols=train.columns \n",
    "# Calculates pearson co-efficient for all combinations，通常认为相关系数大于0.5的为强相关\n",
    "data_corr = train.corr().abs()\n",
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "# Mask unimportant features\n",
    "sns.heatmap(data_corr, mask=data_corr < 1, cbar=False)\n",
    "plt.show()\n",
    "\n",
    "#Set the threshold to select only highly correlated attributes\n",
    "threshold = 0.5\n",
    "# List of pairs along with correlation above threshold\n",
    "corr_list = []\n",
    "size = data_corr.shape[0]\n",
    "#Search for the highly correlated pairs\n",
    "for i in range(0, size): #for 'size' features\n",
    "    for j in range(i+1,size): #avoid repetition\n",
    "        if (data_corr.iloc[i,j] >= threshold and data_corr.iloc[i,j] < 1) or (data_corr.iloc[i,j] < 0 and data_corr.iloc[i,j] <= -threshold):\n",
    "            corr_list.append([data_corr.iloc[i,j],i,j]) #store correlation and columns index\n",
    "#Sort to show higher ones first            \n",
    "s_corr_list = sorted(corr_list,key=lambda x: -abs(x[0]))\n",
    "#Print correlations and column names\n",
    "for v,i,j in s_corr_list:\n",
    "    print (\"%s and %s = %.2f\" % (cols[i],cols[j],v))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上图可见，特征弱相关，保留特征"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3、Logistic回归，并选择最佳的正则函数（L1/L2）及正则参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据标准化\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# 初始化特征的标准化器\n",
    "ss_X = StandardScaler()\n",
    "\n",
    "# 分别对训练和测试数据的特征进行标准化处理\n",
    "X_train = ss_X.fit_transform(X_train)\n",
    "#X_test = ss_X.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(614, 8)"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(614,)"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "default Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "lr= LogisticRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "logloss of each fold is:  [0.46129644 0.46510588 0.56426612 0.44377717 0.46617809]\n",
      "cv logloss is: 0.48012474004701106\n"
     ]
    }
   ],
   "source": [
    "# 交叉验证用于评估模型性能和进行参数调优（模型选择）\n",
    "#分类任务中交叉验证缺省是采用StratifiedKFold\n",
    "from sklearn.cross_validation import cross_val_score\n",
    "loss = cross_val_score(lr, X_train, y_train, cv=5, scoring='neg_log_loss')\n",
    "print('logloss of each fold is: ',-loss)\n",
    "print('cv logloss is:', -loss.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "正则化的 Logistic Regression及参数调优"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score='raise',\n",
       "       estimator=LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
       "          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
       "          verbose=0, warm_start=False),\n",
       "       fit_params=None, iid=True, n_jobs=1,\n",
       "       param_grid={'penalty': ['l1', 'l2'], 'C': [0.001, 0.01, 0.1, 1, 10, 100, 1000]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, return_train_score='warn',\n",
       "       scoring='neg_log_loss', verbose=0)"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "#需要调优的参数\n",
    "# 请尝试将L1正则和L2正则分开，并配合合适的优化求解算法（slover）\n",
    "#tuned_parameters = {'penalty':['l1','l2'],\n",
    "#                   'C': [0.001, 0.01, 0.1, 1, 10, 100, 1000]\n",
    "#                   }\n",
    "penaltys = ['l1','l2']\n",
    "Cs = [0.001, 0.01, 0.1, 1, 10, 100, 1000]\n",
    "tuned_parameters = dict(penalty = penaltys, C = Cs)\n",
    "\n",
    "lr_penalty= LogisticRegression()\n",
    "grid= GridSearchCV(lr_penalty, tuned_parameters,cv=5, scoring='neg_log_loss')\n",
    "grid.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('mean_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split0_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split1_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split2_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split3_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split4_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('std_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'mean_fit_time': array([0.00200334, 0.00240283, 0.00180149, 0.00280151, 0.00620193,\n",
       "        0.00480204, 0.00300188, 0.0034019 , 0.00420341, 0.00340219,\n",
       "        0.0036026 , 0.00400314, 0.00300322, 0.00240097]),\n",
       " 'mean_score_time': array([0.0020009 , 0.00320201, 0.00180354, 0.00320449, 0.00220451,\n",
       "        0.00280204, 0.00240188, 0.00220127, 0.00440269, 0.00340214,\n",
       "        0.00300393, 0.00240107, 0.00220208, 0.00220251]),\n",
       " 'mean_test_score': array([-0.69314718, -0.64214833, -0.6721329 , -0.52844007, -0.48658913,\n",
       "        -0.47999943, -0.4804363 , -0.48017599, -0.48089894, -0.48086932,\n",
       "        -0.48095223, -0.48095123, -0.48095667, -0.48095956]),\n",
       " 'mean_train_score': array([-0.69314718, -0.6412946 , -0.67079105, -0.52380684, -0.47502559,\n",
       "        -0.46674403, -0.46228805, -0.46214818, -0.46206768, -0.46206619,\n",
       "        -0.46206531, -0.4620653 , -0.46206529, -0.46206529]),\n",
       " 'param_C': masked_array(data=[0.001, 0.001, 0.01, 0.01, 0.1, 0.1, 1, 1, 10, 10, 100,\n",
       "                    100, 1000, 1000],\n",
       "              mask=[False, False, False, False, False, False, False, False,\n",
       "                    False, False, False, False, False, False],\n",
       "        fill_value='?',\n",
       "             dtype=object),\n",
       " 'param_penalty': masked_array(data=['l1', 'l2', 'l1', 'l2', 'l1', 'l2', 'l1', 'l2', 'l1',\n",
       "                    'l2', 'l1', 'l2', 'l1', 'l2'],\n",
       "              mask=[False, False, False, False, False, False, False, False,\n",
       "                    False, False, False, False, False, False],\n",
       "        fill_value='?',\n",
       "             dtype=object),\n",
       " 'params': [{'C': 0.001, 'penalty': 'l1'},\n",
       "  {'C': 0.001, 'penalty': 'l2'},\n",
       "  {'C': 0.01, 'penalty': 'l1'},\n",
       "  {'C': 0.01, 'penalty': 'l2'},\n",
       "  {'C': 0.1, 'penalty': 'l1'},\n",
       "  {'C': 0.1, 'penalty': 'l2'},\n",
       "  {'C': 1, 'penalty': 'l1'},\n",
       "  {'C': 1, 'penalty': 'l2'},\n",
       "  {'C': 10, 'penalty': 'l1'},\n",
       "  {'C': 10, 'penalty': 'l2'},\n",
       "  {'C': 100, 'penalty': 'l1'},\n",
       "  {'C': 100, 'penalty': 'l2'},\n",
       "  {'C': 1000, 'penalty': 'l1'},\n",
       "  {'C': 1000, 'penalty': 'l2'}],\n",
       " 'rank_test_score': array([14, 12, 13, 11, 10,  1,  3,  2,  5,  4,  7,  6,  8,  9]),\n",
       " 'split0_test_score': array([-0.69314718, -0.64371675, -0.66946739, -0.52816851, -0.48618057,\n",
       "        -0.4678555 , -0.46346388, -0.46129644, -0.46108765, -0.46088502,\n",
       "        -0.46086634, -0.4608487 , -0.46084514, -0.46084513]),\n",
       " 'split0_train_score': array([-0.69314718, -0.64085132, -0.66189542, -0.52529099, -0.47823787,\n",
       "        -0.47085398, -0.46684306, -0.46669378, -0.4666238 , -0.46662226,\n",
       "        -0.46662151, -0.46662149, -0.46662149, -0.46662148]),\n",
       " 'split1_test_score': array([-0.69314718, -0.64113725, -0.67517494, -0.52518603, -0.47167216,\n",
       "        -0.47077815, -0.46426796, -0.46510588, -0.46463575, -0.46473286,\n",
       "        -0.46468736, -0.46469927, -0.46469098, -0.46469595]),\n",
       " 'split1_train_score': array([-0.69314718, -0.64188719, -0.67797602, -0.52532854, -0.47970412,\n",
       "        -0.47076994, -0.46692669, -0.46678157, -0.4667161 , -0.4667146 ,\n",
       "        -0.4667139 , -0.46671388, -0.46671388, -0.46671388]),\n",
       " 'split2_test_score': array([-0.69314718, -0.64575466, -0.6680453 , -0.5512625 , -0.54752879,\n",
       "        -0.54301469, -0.56468748, -0.56426612, -0.5684693 , -0.56834734,\n",
       "        -0.56880238, -0.56879096, -0.56882903, -0.5688357 ]),\n",
       " 'split2_train_score': array([-0.69314718, -0.63908575, -0.66162164, -0.5135644 , -0.45564673,\n",
       "        -0.44783203, -0.44194651, -0.44184498, -0.44173183, -0.44173047,\n",
       "        -0.44172922, -0.4417292 , -0.44172919, -0.44172919]),\n",
       " 'split3_test_score': array([-0.69314718, -0.63856226, -0.67581323, -0.50975335, -0.4550309 ,\n",
       "        -0.44706595, -0.44366111, -0.44377717, -0.44397785, -0.44400066,\n",
       "        -0.44402714, -0.4440332 , -0.44403444, -0.44403656]),\n",
       " 'split3_train_score': array([-0.69314718, -0.64333601, -0.67874616, -0.5309552 , -0.48382492,\n",
       "        -0.47509784, -0.47066692, -0.47052445, -0.4704446 , -0.47044314,\n",
       "        -0.47044228, -0.47044226, -0.47044225, -0.47044225]),\n",
       " 'split4_test_score': array([-0.69314718, -0.64152376, -0.67221592, -0.52767402, -0.47216268,\n",
       "        -0.47104103, -0.46582127, -0.46617809, -0.46606446, -0.46612355,\n",
       "        -0.46612047, -0.4661268 , -0.46612652, -0.46612722]),\n",
       " 'split4_train_score': array([-0.69314718, -0.64131272, -0.67371601, -0.52389506, -0.47771432,\n",
       "        -0.46916638, -0.46505705, -0.46489609, -0.46482207, -0.46482048,\n",
       "        -0.46481965, -0.46481964, -0.46481963, -0.46481963]),\n",
       " 'std_fit_time': array([1.19304619e-06, 4.89064920e-04, 7.47755257e-04, 7.50520611e-04,\n",
       "        6.94252209e-03, 3.31386374e-03, 3.07328854e-06, 4.90154936e-04,\n",
       "        2.92746635e-03, 4.92944222e-04, 1.35654457e-03, 2.28255015e-03,\n",
       "        6.34979456e-04, 4.90778297e-04]),\n",
       " 'std_score_time': array([0.00063203, 0.0024819 , 0.00074671, 0.00248262, 0.00097994,\n",
       "        0.00116559, 0.00102   , 0.00040069, 0.00257639, 0.00185636,\n",
       "        0.00209878, 0.00049255, 0.0004003 , 0.00039876]),\n",
       " 'std_test_score': array([0.        , 0.00243715, 0.00305426, 0.0132657 , 0.03205913,\n",
       "        0.03276814, 0.04293798, 0.04285084, 0.04453137, 0.04448689,\n",
       "        0.04466701, 0.04466183, 0.04467757, 0.04467945]),\n",
       " 'std_train_score': array([0.        , 0.00138524, 0.00757197, 0.00566626, 0.00992376,\n",
       "        0.00965834, 0.0103336 , 0.01031565, 0.01033124, 0.01033118,\n",
       "        0.01033136, 0.01033136, 0.01033136, 0.01033136])}"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view the complete results (list of named tuples)\n",
    "grid.cv_results_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.4799994349368312\n",
      "{'C': 0.1, 'penalty': 'l2'}\n"
     ]
    }
   ],
   "source": [
    "# examine the best model\n",
    "print(-grid.best_score_)\n",
    "print(grid.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('mean_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "D:\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('std_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225eab9e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#pd.DataFrame(grid.cv_results_).to_csv('LogisticGridSearchCV_Otto.csv')\n",
    "#cvresult = pd.DataFrame.from_csv('LogisticGridSearchCV_Otto.csv')\n",
    "#test_means = cv_results['mean_test_score']\n",
    "#test_stds = cv_results['std_test_score'] \n",
    "#train_means = cvresult['mean_train_score']\n",
    "#train_stds = cvresult['std_train_score'] \n",
    "\n",
    "\n",
    "# plot CV误差曲线\n",
    "test_means = grid.cv_results_[ 'mean_test_score' ]\n",
    "test_stds = grid.cv_results_[ 'std_test_score' ]\n",
    "train_means = grid.cv_results_[ 'mean_train_score' ]\n",
    "train_stds = grid.cv_results_[ 'std_train_score' ]\n",
    "\n",
    "\n",
    "# plot results\n",
    "n_Cs = len(Cs)\n",
    "number_penaltys = len(penaltys)\n",
    "test_scores = np.array(test_means).reshape(n_Cs,number_penaltys)\n",
    "train_scores = np.array(train_means).reshape(n_Cs,number_penaltys)\n",
    "test_stds = np.array(test_stds).reshape(n_Cs,number_penaltys)\n",
    "train_stds = np.array(train_stds).reshape(n_Cs,number_penaltys)\n",
    "\n",
    "x_axis = np.log10(Cs)\n",
    "for i, value in enumerate(penaltys):\n",
    "    #pyplot.plot(log(Cs), test_scores[i], label= 'penalty:'   + str(value))\n",
    "    pyplot.errorbar(x_axis, test_scores[:,i], yerr=test_stds[:,i] ,label = penaltys[i] +' Test')\n",
    "    pyplot.errorbar(x_axis, train_scores[:,i], yerr=train_stds[:,i] ,label = penaltys[i] +' Train')\n",
    "    \n",
    "pyplot.legend()\n",
    "pyplot.xlabel( 'log(C)' )                                                                                                      \n",
    "pyplot.ylabel( 'neg-logloss' )\n",
    "pyplot.savefig('LogisticGridSearchCV_C.png' )\n",
    "\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4、线性SVM，并选择最佳正则参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import LinearSVC\n",
    "from sklearn.svm import SVC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit_grid_point_Linear(C, X_train, y_train, X_test, y_test):\n",
    "    \n",
    "    # 在训练集是那个利用SVC训练\n",
    "    SVC2 =  LinearSVC( C = C)\n",
    "    SVC2 = SVC2.fit(X_train, y_train)\n",
    "    \n",
    "    # 在校验集上返回accuracy\n",
    "    accuracy = SVC2.score(X_test, y_test)\n",
    "    \n",
    "    print(\"accuracy: {}\".format(accuracy))\n",
    "    return accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy: 0.35064935064935066\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225ec9128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#需要调优的参数\n",
    "C_s = np.logspace(-3, 3, 7)# logspace(a,b,N)把10的a次方到10的b次方区间分成N份  \n",
    "#penalty_s = ['l1','l2']\n",
    "\n",
    "accuracy_s = []\n",
    "for i, oneC in enumerate(C_s):\n",
    "#    for j, penalty in enumerate(penalty_s):\n",
    "    tmp = fit_grid_point_Linear(oneC, X_train, y_train, X_test, y_test)\n",
    "    accuracy_s.append(tmp)\n",
    "\n",
    "x_axis = np.log10(C_s)\n",
    "#for j, penalty in enumerate(penalty_s):\n",
    "pyplot.plot(x_axis, np.array(accuracy_s), 'b-')\n",
    "    \n",
    "pyplot.legend()\n",
    "pyplot.xlabel( 'log(C)' )                                                                                                      \n",
    "pyplot.ylabel( 'accuracy' )\n",
    "pyplot.savefig('SVM_Otto.png' )\n",
    "\n",
    "pyplot.show()\n",
    "  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5、RBF核的SVM，并选择最佳的超参数（正则参数、RBF核函数宽度）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit_grid_point_RBF(C, gamma, X_train, y_train, X_test, y_test):\n",
    "    \n",
    "    # 在训练集是那个利用SVC训练\n",
    "    SVC3 =  SVC( C = C, kernel='rbf', gamma = gamma)\n",
    "    SVC3 = SVC3.fit(X_train, y_train)\n",
    "    \n",
    "    # 在校验集上返回accuracy\n",
    "    accuracy = SVC3.score(X_test, y_test)\n",
    "    \n",
    "    print(\"accuracy: {}\".format(accuracy))\n",
    "    return accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n"
     ]
    }
   ],
   "source": [
    "#需要调优的参数\n",
    "C_s = np.logspace(-2, 2, 5)# logspace(a,b,N)把10的a次方到10的b次方区间分成N份 \n",
    "gamma_s = np.logspace(-2, 2, 5)  \n",
    "\n",
    "accuracy_s = []\n",
    "for i, oneC in enumerate(C_s):\n",
    "    for j, gamma in enumerate(gamma_s):\n",
    "        tmp = fit_grid_point_RBF(oneC, gamma, X_train, y_train, X_test, y_test)\n",
    "        accuracy_s.append(tmp)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.6363636363636364\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.34415584415584416\n",
      "accuracy: 0.36363636363636365\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.35714285714285715\n",
      "accuracy: 0.6428571428571429\n",
      "accuracy: 0.35714285714285715\n"
     ]
    }
   ],
   "source": [
    "#需要调优的参数\n",
    "C_s = np.logspace(-1, 2, 4)# logspace(a,b,N)把10的a次方到10的b次方区间分成N份 \n",
    "gamma_s = np.logspace(-5, -2, 4)  \n",
    "\n",
    "accuracy_s = []\n",
    "for i, oneC in enumerate(C_s):\n",
    "    for j, gamma in enumerate(gamma_s):\n",
    "        tmp = fit_grid_point_RBF(oneC, gamma, X_train, y_train, X_test, y_test)\n",
    "        accuracy_s.append(tmp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f225f6dbe0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "accuracy_s1 =np.array(accuracy_s).reshape(len(C_s),len(gamma_s))\n",
    "x_axis = np.log10(C_s)\n",
    "for j, gamma in enumerate(gamma_s):\n",
    "    pyplot.plot(x_axis, np.array(accuracy_s1[:,j]), label = ' Test - log(gamma)' + str(np.log10(gamma)))\n",
    "\n",
    "pyplot.legend()\n",
    "pyplot.xlabel( 'log(C)' )                                                                                                      \n",
    "pyplot.ylabel( 'accuracy' )\n",
    "pyplot.savefig('RBF_SVM_Otto.png' )\n",
    "\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
